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Description
Introduction
Spectral indices can determine biomass differences in plant canopies. The indices react differently sensitive to differences in biomass and chlorophyll content in different growth stages (Hunt et.al. 2005; Voitik et.al. 2023). This study explores the potential of the NGRDI for vegetation monitoring as an alternative to other well established indices. A focus was set to the sensitivity of the NGRDI at different times during the vegetation of winter grain in two years. Additionally, NGRDI from aerial photos were correlated with satellite data.
According to Choudhary et.al. (2021) the NGRDI shows a correlation with the Normalized Difference Vegetation Index (NDVI). The Normalized Difference Red-Edge Index (NDRE) shows a correlation with the NDVI with a better vegetation monitoring in later growth stages (Naguib et.al. 2022; Voitik et.al. 2023).
Material and Methods
The research was conducted on a field in North-East Germany. Covering the vegetation period of winter wheat 2021/2022 and winter barley 2022/2023, aerial photos of this field were taken with a digital camera at five dates. Corresponding sky clear images from the Sentinel 2-satellite were analysed. A date in mid-October was targeted to capture the pre-winter development. Recordings in April, May and June should capture the vegetation development after winter until harvest. The NGRDI was calculated based on the red and green spectral bands of the aerial photos and satellite images. The combined yield data of winter barley from 2023 were used. For 2022, no yield data was available due to data loss. The information of the calculated indices at different times as well as the yield data were assigned to randomly distributed points covering the field. Regression analyses were performed to evaluate the respective correlations.
Results
Emphasis was placed on the NGRDI to achieve a first transferability to the aerial photos. The NGRDI of the satellite images was strongly correlated to the NDVI. In October and April, the NDRE is strongly correlated with the NGRDI. The NDRE showed a reduction in the otherwise strong correlation with the NDVI at the beginning of May. The values of the NGRDI from the sensors satellite image and aerial image correlated moderately with each other in April and June. Until May the satellite and aerial indices correlated moderately with the yield data. In June the satellite indices are strongly correlated to the yield data. The comparison between the index data from 2022 with the index and yield data from 2023 showed moderate to strong correlations at different dates.
Discussion
The correlations between NGRDI and NDVI as well as between NDVI and NDRE found in previous studies were retrieved in the comparison of the satellite index data. The loss of correlation between the NDRE and NDVI could be explained by the higher chlorophyll sensitivity of the NDRE. The NDVI is said to get a saturation in increasing growth stages (Naguib et.al. 2022). The unsteady correlation between the satellite- and aerial-sensor based NGRDI over the vegetation period could be explained by atmospheric influences and the angle of the inclined original image affecting the quality of the aerial image. Nonetheless, the NGRDI aerial images showed useful visual information about different crop development within the field and correlations with the yield data.
References
Choudhary, S.S., Biswal, S., Saha, R. et al. A non-destructive approach for assessment of nitrogen status of wheat crop using unmanned aerial vehicle equipped with RGB camera. Arabian Journal of Geosciences 14, 1739 (2021).
Hunt, E.R., Cavigelli, M., Daughtry, C.S.T. et al. (2005). Evaluation of Digital Photography from Model Aircraft for Remote Sensing of Crop Biomass and Nitrogen Status. Precision Agric 6, 359–378.
Naguib, N.S., Daliman, S. (2022). Analysis of NDVI and NDRE Indices Using Satellite Images for Crop Identification at Kelantan. 4th International Conference on Tropical Resources and Sustainable Sciences 2022 IOP Conf. Series: Earth and Environmental Science, 1102, 012054.
Voitik, A., Kravchenko, V., Pushka, O., et.al. (2023). Comparison of NDVI, NDRE, MSAVI and NDSI Indices for Early Diagnosis of Crop Problems. Agricultural Engineering. 27. 47-57.
| Keywords | NGRDI; Sentinel 2; aerial photography; biomass heterogeneity |
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